Physical parameters reconstruction of a fixed–fixed mass-spring system from its characteristic data

AbstractIn this paper, an inverse problem of constructing a linear n degree of freedom mass-spring system from part of its physical parameters and part of modality of its maximal or minimal natural frequencies is considered. The solvability and the expression of the solution is derived. The numerical algorithms and some numerical examples are given

Dynamic response analysis in bolted joint structure with viscoelastic layer and experimental investigations

In this paper, the dynamic response characteristics of a common double shear lap joint structure with viscoelastic layer are investigated. Firstly, an analytical model is established in shear vibration based on phenomenological model. The fourth order Runge-Kutta method is employed to calculate the harmonic response, where the effect of Coulomb friction and excitation levels on system are presented. Secondly, a new nonlinear finite element model for the bolted joint structure with viscoelastic layer is developed. The simulation results show good agreement with the corresponding experimental results. Finally, the proposed harmonic excitation experiments with laser vibrometer in tangential direction are carried out to investigate the nonlinear behaviors of system, as well as the influence of bolt preload and viscoelastic material on dynamic characteristics of the bolted joint beam. The results show that the viscoelastic layer help reduce vibration at certain extent, especially in the high frequency region of vibration, and some peak frequencies of system can be changed through the viscoelastic layer

Trend of myopia through different interventions from 2010 to 2050: Findings from Eastern Chinese student surveillance study

PurposeFirst, to investigate the utilization rate and effect of proven myopic interventions. Second, to predict the prevalence of myopia and high myopia, as well as Years Lived with Disability (YLD) caused by an uncorrected refractive error in children and teens in Eastern China from 2010 to 2050 under different interventions.Methods(1) The surveillance of common diseases among children and adolescents in Jiangsu Province from 2010 to 2021 provides the database for myopia screening and intervention utilization surveys. (2) The National Bureau of Statistics and the Global Burden of Disease Study 2016 (GBD2016) are the foundation for the estimated myopes and YLD. (3) A systematic review provides the strong or weak impact of intervention in the prediction model. (4) The trend of screening myopia from 2010 to 2050 under various treatments is predicted using a GM (1,1) model.ResultsBy the year 2050, myopia is expected to affect 8,568,305 (7–12 years old) and 15,766,863 (13–18 years old) children and adolescents, respectively (95% CI: 8,398,977–8,737,633). The utilization prevalence of myopia-proven interventions for myopic children included outdoor activities, orthokeratology lenses, atropine treatment, contact lenses, frame glasses, and eye exercises, with respective rates of 31.9–33.1, 2.1–2.3, 6.0–7.5, 2.2–2.7, 60.4–62.2, and 64.7–72.5%. All interventions have substantial effects on myopia after parental myopia and behavior pattern adjustment, including physical activity, near work, dietary pattern, and sleep. Under strong intervention, the estimated reduced myopia prevalence by the year 2050 is 1,259,086 (95% CI: 1,089,758–1,428,414) for children aged 7–12, and 584,785 (95% CI: 562,748–606,823) for children aged 13–18, respectively.ConclusionAmong myopic Chinese children and adolescents, the use rates and effects of proven myopia interventions vary. Under the present intervention strategy, the prevalence of myopia and high myopia will increase from 2010 to 2050. The overall number of myopic people can be greatly decreased by implementing timely, steady, comprehensive interventions

CO2 emission patterns in shrinking and growing cities:A case study of Northeast China and the Yangtze River Delta

The implementation of CO2 emission mitigation policies in cities is the key to China achieving its national emission mitigation targets. China is experiencing rapid urbanization and facing huge inequality in regional development and then shrinking cities generate. This study, for the first time, discusses long-term CO2 emission patterns of shrinking cities with comparisons of growing cities. 55 cities in Northeast China and the Yangtze River Delta are selected as cases. We first categorize these cities into three groups of shrinking cities and three groups of growing cities with a population index. Each group's emission patterns in terms of energy, employment and industry structures are then examined. We find that CO2 emissions in the rapidly shrinking group presented a continuously increasing trend, while the other five groups reached their emission peaks in 2011-2013. For slightly and moderately shrinking groups, CO2 emission mitigation was a positive sign but occurred with the decline of secondary industry, especially for resource-based or heavy manufacturing cities, such as Daqing and Anshan in Northeast China. In the case of three types of growing cities, cities were capable of mitigating CO2 emissions and maintaining economic growth. The slightly growing group was the optimal type among these six groups. Its CO2 emissions experienced a decline with an annual rate of -1.47% during 2013-2015, while the economy still soared (increased by 7.27% annually). New economic growth points should be fostered to mitigate further shrinkage and achieve sustainable development for shrinking cities. The cities' categorization rules, research thinking, and results offered in this study could provide a reference for other cities or developing countries at similar industrialization/urbanization phases to abbreviate their path towards a low-carbon economy

Penerapan Pendekatan Pengajaran Terbalik (Reciprocal Teaching) Untuk Meningkatkan Kemandirian Belajar Biologi Siswa Kelas Vii-g SMP N 5 Karanganyar Tahun Pelajaran 2010/ 2011

– The objective of this study is to improve student independence in learning biology by implementing Inverted Teaching Approach (Reciprocal Teaching) on Environmental Management material. This research is a classroom action research. This research was conducted in two cycles. Each cycle consisted of planning, implementation of the action,observation, and reflection. The subjects of the study were VII-G class students of SMP Negeri 5 Karanganyar in the academic year of 2010/2011. The number of the students was 32. The technique and instrumen of collectiing data were questionnaire, observation, and interviews. The technique of analyzing data was descriptive analysis techniques. Triangulation technique was used in data validation. The results proved that by implementing Inverted Teaching Approach (Reciprocal Teaching) students\u27 independence in learning biology enhanced. It is based on the results of questionnaires, observations and interviews. The questionnaire of students\u27 learning independence showed that the mean percentage of students\u27 achievement in each indicator in pre-cycle, cycle I, and cycle II was 67.97%, 72.55%, and 77.58% respectively. The observation of students\u27 learning independence showed that the mean percentage of students\u27 achievement in each indicator in pre-cycle, cycle I, and cycle II was 39.68%, 67.5%, and 80.62% respectively. It can be concluded that the implementation of Inverted Teaching Approach (Reciprocal Teaching) can enhance students learning independence

BertNet: Harvesting Knowledge Graphs with Arbitrary Relations from Pretrained Language Models

It is crucial to automatically construct knowledge graphs (KGs) of diverse new relations to support knowledge discovery and broad applications. Previous KG construction methods, based on either crowdsourcing or text mining, are often limited to a small predefined set of relations due to manual cost or restrictions in text corpus. Recent research proposed to use pretrained language models (LMs) as implicit knowledge bases that accept knowledge queries with prompts. Yet, the implicit knowledge lacks many desirable properties of a full-scale symbolic KG, such as easy access, navigation, editing, and quality assurance. In this paper, we propose a new approach of harvesting massive KGs of arbitrary relations from pretrained LMs. With minimal input of a relation definition (a prompt and a few shot of example entity pairs), the approach efficiently searches in the vast entity pair space to extract diverse accurate knowledge of the desired relation. We develop an effective search-and-rescore mechanism for improved efficiency and accuracy. We deploy the approach to harvest KGs of over 400 new relations from different LMs. Extensive human and automatic evaluations show our approach manages to extract diverse accurate knowledge, including tuples of complex relations (e.g., "A is capable of but not good at B"). The resulting KGs as a symbolic interpretation of the source LMs also reveal new insights into the LMs' knowledge capacities.Comment: ACL 2023 (Findings); Code available at https://github.com/tanyuqian/knowledge-harvest-from-lm